Bill R. Miller

Bio: Bill R. Miller is an academic researcher from University of Florida. The author has contributed to research in topics: Host cell surface & Loss function. The author has an hindex of 4, co-authored 4 publications receiving 1805 citations.

MMPBSA.py: An Efficient Program for End-State Free Energy Calculations.

Abstract: MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson–Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, rele...

Wide-Open Flaps are Key to Urease Activity

Abstract: Substrate ingress and product egress from the active site of urease is tightly controlled by an active-site flap. Molecular dynamics simulations of urease have revealed a previously unobserved wide-open flap state that, unlike the well-characterized closed and open states, allows ready access to the metal cluster in the active site. This state is easily reached from the open state via low free energy barriers. Additionally, we have found that even when the flap is closed, a region of the binding pocket is solvent-exposed, leading to the hypothesis that it may act as a substrate/product reservoir. The newly identified wide-open state offers further opportunities for small-molecule drug discovery by defining a more extensive active-site pocket than has been previously described.

Trypanosoma cruzi trans-sialidase as a drug target against Chagas disease (American trypanosomiasis)

Abstract: Chagas disease (or American trypanosomiasis) is a deadly tropical disease that affects millions of people worldwide, primarily in rural regions of South America. Trypanosoma cruzi, the parasitic cause of Chagas disease, possesses a membrane-anchored trans-sialidase enzyme that transfers sialic acids from the host cell surface to the parasitic cell surface, allowing T. cruzi to effectively evade the host‘s immune system. This enzyme has no analogous human counterpart and thus has become an interesting drug target to combat the parasite. Recent computational efforts have improved our knowledge about the enzyme‘s structure, dynamics and catalyzed reaction. Many compounds have been tested against trans-sialidase activity, but no strong inhibitors have been identified yet. The current lack of drugs for Chagas disease necessitates more R&D into the design and discovery of strong inhibitors of T. cruzi trans-sialidase.

Design of e-pharmacophore models using compound fragments for the trans-sialidase of Trypanosoma cruzi: screening for novel inhibitor scaffolds.

Abstract: Chagas’ is a fatal disease that affects millions of people worldwide. The lack of safe and effective treatments for Chagas’ highlights the need for the discovery of new drugs to fight the disease. Trypanosoma cruzi, the parasitic cause of Chagas’ disease, synthesizes a trans-sialidase (TcTS) enzyme responsible for the transfer of sialic acids from the host cell surface to glycoconjugates on the parasitic cell surface. TcTS has no human analogs and is vital to the life cycle of T. cruzi, making TcTS an important enzyme for drug design against Chagas’ disease. We use fragment docking to generate various e-pharmacophore hypotheses depicting protein residues important for ligand binding. Virtual screening of the ZINC Clean Leads database with more than 4 million compounds using the e-pharmacophore models found 82 potential inhibitors of TcTS. Molecular dynamics and free energy of binding calculations were used to rank the compounds based on their affinity for TcTS. Two compounds—ZINC13359679 and ZINC02576132—were found to be the most promising lead candidates for TcTS inhibition, and their binding modes are analyzed in detail.

Alleles of unc‐33/CRMP exhibit defects during Caenorhabditis elegans epidermal morphogenesis

Abstract: Microtubule‐associated proteins regulate the dynamics, organization, and function of microtubules, impacting a number of vital cellular processes. CRMPs have been shown to control microtubule assembly and axon outgrowth during neuronal differentiation. While many microtubule‐associated proteins have been linked to roles in cell division and neuronal development, it is still unclear the complement that control the formation of parallel microtubule arrays in epithelial cells.

PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data

Abstract: We describe PTRAJ and its successor CPPTRAJ, two complementary, portable, and freely available computer programs for the analysis and processing of time series of three-dimensional atomic positions (i.e., coordinate trajectories) and the data therein derived. Common tools include the ability to manipulate the data to convert among trajectory formats, process groups of trajectories generated with ensemble methods (e.g., replica exchange molecular dynamics), image with periodic boundary conditions, create average structures, strip subsets of the system, and perform calculations such as RMS fitting, measuring distances, B-factors, radii of gyration, radial distribution functions, and time correlations, among other actions and analyses. Both the PTRAJ and CPPTRAJ programs and source code are freely available under the GNU General Public License version 3 and are currently distributed within the AmberTools 12 suite of support programs that make up part of the Amber package of computer programs (see http://ambe...

The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

Abstract: Introduction: The molecular mechanics energies combined with the Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor–ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success.Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications.Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used success...

End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

Abstract: Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are arguably very popular methods for binding free energy prediction since they are more accurate than most scoring functions of molecular docking and less computationally demanding than alchemical free energy methods. MM/PBSA and MM/GBSA have been widely used in biomolecular studies such as protein folding, protein-ligand binding, protein-protein interaction, etc. In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed. The latest applications of MM/GBSA and MM/PBSA in drug design are also presented. This review intends to provide readers with guidance for practically applying MM/PBSA and MM/GBSA in drug design and related research fields.

Isolation of SARS-CoV-2-related coronavirus from Malayan pangolins.

Abstract: The current outbreak of coronavirus disease-2019 (COVID-19) poses unprecedented challenges to global health1. The new coronavirus responsible for this outbreak-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-shares high sequence identity to SARS-CoV and a bat coronavirus, RaTG132. Although bats may be the reservoir host for a variety of coronaviruses3,4, it remains unknown whether SARS-CoV-2 has additional host species. Here we show that a coronavirus, which we name pangolin-CoV, isolated from a Malayan pangolin has 100%, 98.6%, 97.8% and 90.7% amino acid identity with SARS-CoV-2 in the E, M, N and S proteins, respectively. In particular, the receptor-binding domain of the S protein of pangolin-CoV is almost identical to that of SARS-CoV-2, with one difference in a noncritical amino acid. Our comparative genomic analysis suggests that SARS-CoV-2 may have originated in the recombination of a virus similar to pangolin-CoV with one similar to RaTG13. Pangolin-CoV was detected in 17 out of the 25 Malayan pangolins that we analysed. Infected pangolins showed clinical signs and histological changes, and circulating antibodies against pangolin-CoV reacted with the S protein of SARS-CoV-2. The isolation of a coronavirus from pangolins that is closely related to SARS-CoV-2 suggests that these animals have the potential to act as an intermediate host of SARS-CoV-2. This newly identified coronavirus from pangolins-the most-trafficked mammal in the illegal wildlife trade-could represent a future threat to public health if wildlife trade is not effectively controlled.